An optimized reconfiguration technique of photovoltaic array using adaptive-JAYA optimization
It is proved that the proposed Adaptive-JAYA approach improves the output power by 26.12%, 22.20%, 7.61%, and 7.68% compared to the TCT for the four shading patterns, i.e. SW, LW, SN, and LN.
Abstract
ABSTRACT Reconfiguration of PV array has emerged as a promising solution to improve the power under partial shading conditions (PSC). The three main reconfiguration techniques are the physical array relocation method, electrical array reconfiguration (EAR), and the switching matrix generation based on optimization. The physical relocation techniques are complicated as they require hard labor. In the case of EAR, the optimal design of the switching matrix is still challenging. Therefore, to overcome these issues, this paper proposes a recent metaheuristic technique of Adaptive-JAYA optimization for the optimum reconfiguration of the PV array. Adaptive-JAYA is chosen for its simplicity and reliability, which makes it consume less memory, reducing the burden on processors. The proposed approaches are applied on a 9 × 9 PV array under eight shading patterns and also on a 9 × 15 PV array to analyze the competency of the proposed approach on unsymmetrical shading. The MATLAB results are quantitatively analyzed, and a comprehensive comparison is performed with many existing reconfiguration techniques. It is proved that the proposed Adaptive-JAYA approach improves the output power by 26.12%, 22.20%, 7.61%, and 7.68% compared to the TCT for the four shading patterns, i.e. SW, LW, SN, and LN.